CUDA.jl
CUDA programming in Julia. (by JuliaGPU)
Rust-CUDA
Ecosystem of libraries and tools for writing and executing fast GPU code fully in Rust. (by Rust-GPU)
| CUDA.jl | Rust-CUDA | |
|---|---|---|
| 15 | 39 | |
| 1,266 | 3,838 | |
| 2.5% | 18.4% | |
| 9.5 | 6.7 | |
| 3 days ago | 5 days ago | |
| Julia | Rust | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
CUDA.jl
Posts with mentions or reviews of CUDA.jl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-01.
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Ask HN: Best way to learn GPU programming?
It would also mean learning Julia, but you can write GPU kernels in Julia and then compile for NVidia CUDA, AMD ROCm or IBM oneAPI.
https://juliagpu.org/
I've written CUDA kernels and I knew nothing about it going in.
- What's your main programming language?
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How is Julia Performance with GPUs (for LLMs)?
See https://juliagpu.org/
- Yann Lecun: ML would have advanced if other lang had been adopted versus Python
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C++ is making me depressed / CUDA question
If you just want to do some numerical code that requires linear algebra and GPU, your best bet would be Julia or Python+JAX.
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Parallélisation distribuée presque triviale d’applications GPU et CPU basées sur des Stencils avec…
GitHub - JuliaGPU/CUDA.jl: CUDA programming in Julia.
- Why Fortran is easy to learn
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Generic GPU Kernels
Should have (2017) in the title.
Indeed cool to program julia directly on the GPU and Julia on GPU and this has further evolved since then, see https://juliagpu.org/
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Announcing The Rust CUDA Project; An ecosystem of crates and tools for writing and executing extremely fast GPU code fully in Rust
I'm excited to eventually see something like JuliaGPU with support for multiple backends.
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[Media] 100% Rust path tracer running on CPU, GPU (CUDA), and OptiX (for denoising) using one of my upcoming projects. There is no C/C++ code at all, the program shares a single rust crate for the core raytracer and uses rust for the viewer and renderer.
That's really cool! Have you looked at CUDA.jl for the Julia language? Maybe you could take some ideas from there. I am pretty sure it does the same thing you do here, and they support any arbitrary code with the limitations that you cannot allocate memory, I/O is disallowed, and badly-typed code(dynamic) will not compile.
Rust-CUDA
Posts with mentions or reviews of Rust-CUDA.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2025-03-14.
- Exo: Exocompilation for productive programming of hardware accelerators
- Introduction to CUDA Programming for Python Developers
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[Media] Anyone try writing a ray tracer with rust? It's pretty fun!
Source code [here](https://github.com/ihawn/RTracer) if anyone is interested in taking a look or giving feedback. As a side question, does anyone have any general advise on getting GPU compute working with rust? I tried [this project](https://github.com/Rust-GPU/Rust-CUDA) but had a bunch of issues (And it doesn't look like an active repo anyways)
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Is rust or python better for Machine learning? Or is there enough decent frameworks?
You have this https://github.com/Rust-GPU/Rust-CUDA
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toolchain nightly package building issue
What I'm trying to do is check out https://github.com/Rust-GPU/Rust-CUDA for a class project.
- [Rust] État de GPGPU en 2022
- Which crate for CUDA in Rust?
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Announcing cudarc and fully GPU accelerated dfdx: ergonomic deep learning ENTIRELY in rust, now with CUDA support and tensors with mixed compile and runtime dimensions!
Be warned, NON_BLOCKING streams do not fully synchronize with sync host to device copies. They are not guaranteed to actually finish by the time they return. Meaning its possible to initiate a copy, then initiate a kernel launch, and have the copy be unfinished by the time the kernel is launched. This caused so many confusing bugs that i personally decided to stop using NON_BLOCKING altogether in rust-cuda. https://github.com/Rust-GPU/Rust-CUDA/issues/15
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In which circumstances is C++ better than Rust?
- Cuda is not doing by FFI linking, instead is compiling CUDA code natively in Rust https://github.com/Rust-GPU/Rust-CUDA and even if it not complete as the C++ SDK is more than a toy
- I learned 7 programming languages so you don't have to
What are some alternatives?
When comparing CUDA.jl and Rust-CUDA you can also consider the following projects:
cupynumeric - An Aspiring Drop-In Replacement for NumPy at Scale
rust-gpu - 🐉 Making Rust a first-class language and ecosystem for GPU shaders 🚧
awesome-quant - A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
rust-ndarray - ndarray: an N-dimensional array with array views, multidimensional slicing, and efficient operations
GPUCompiler.jl - Reusable compiler infrastructure for Julia GPU backends.
wgpu - A cross-platform, safe, pure-Rust graphics API.